Examples with HaiQae jcog.learn.ql.HaiQae used on opensource projects

Example 1 with HaiQae

use of jcog.learn.ql.HaiQae in project narchy by automenta.

the class TensorGlow method main.

public static void main(String[] args) {
    PhyWall p = SpaceGraph.wall(1200, 1000);
    p.W.setGravity(new v2(0, -2.8f));
    staticBox(p.W, -5, -8, +5, 2f, false, true, true, true);
    for (int j = 0; j < 3; j++) {
        BodyDef bodyDef2 = new BodyDef();
        bodyDef2.type = BodyType.DYNAMIC;
        // otocenie
        bodyDef2.angle = -0.6f;
        // smer pohybu
        bodyDef2.linearVelocity = new v2(0.0f, 0.0f);
        // rotacia (rychlost rotacie)
        bodyDef2.angularVelocity = 0.0f;
        Body2D newBody = p.W.addBody(bodyDef2);
        PolygonShape shape2 = new PolygonShape();
        shape2.setAsBox(0.25f, 0.25f);
        Fixture f = newBody.addFixture(shape2, 1.0f);
        // trenie
        f.friction = 0.5f;
        // odrazivost
        f.restitution = 0.0f;
        f.material = new Uniform();
        f.material.m_rigidity = 1.0f;
    }
    // //ceiling rack
    // addBox(p.W, -1, +0.4f, 0, +0.65f, false, true, true, true);
    // new Pacman(p.W);
    {
        p.W.setContactListener(new Explosives.ExplosionContacts());
        TheoJansen t = new TheoJansen(p.W, 0.35f);
        PhyWall.PhyWindow pw = p.put(new Gridding(0.5f, new Port((float[] v) -> {
            // System.out.println(v);
            t.motorJoint.setMotorSpeed(v[0] * 2 - v[1] * 2);
            t.motorJoint.setMaxMotorTorque(v[2]);
            t.motorJoint.enableLimit(true);
            t.motorJoint.setLimits((float) (-v[3] * Math.PI), (float) (+v[4] * Math.PI));
            if (v[5] > 0.5f) {
                t.gun.fire();
            }
            t.turretJoint.setLimits((float) (+Math.PI / 2 + v[6] * Math.PI - 0.1f), (float) (+Math.PI / 2 + v[6] * Math.PI + 0.1f));
        })), 0.8f, 0.4f);
        p.W.addJoint(new RevoluteJoint(p.W, new RevoluteJointDef(pw.body, t.chassis)));
    }
    {
        p.W.setParticleRadius(0.05f);
        p.W.setParticleDamping(0.1f);
        CircleShape shape = new CircleShape();
        shape.center.set(0, 10);
        shape.radius = 2f;
        ParticleGroupDef pd = new ParticleGroupDef();
        pd.flags = ParticleType.b2_waterParticle;
        // b2_viscousParticle;
        // b2_elasticParticle;
        // b2_springParticle;
        // b2_powderParticle;
        pd.color = new ParticleColor(0.7f, 0.1f, 0.1f, 0.8f);
        pd.shape = shape;
        p.W.addParticles(pd);
    }
    HaiQae q = new HaiQae(8, 2);
    float[] in = new float[q.ae.inputs()];
    final Tensor randomVector = Tensor.randomVectorGauss(in.length, 0, 1, rng);
    final FloatRange lerpRate = new FloatRange(0.01f, 0, 1f);
    final TensorLERP lerpVector = new TensorLERP(randomVector, lerpRate);
    PhyWall.PhyWindow w = p.put(new Gridding(0.25f, new AutoUpdateMatrixView(lerpVector.data), new LabeledPane("lerp", new XYSlider().on((x, y) -> {
        lerpRate.set(x);
    })), new LabeledPane("out", new Port((x) -> {
    }) {

        @Override
        public void prePaint(int dtMS) {
            super.prePaint(dtMS);
            out(lerpVector.data);
        }
    })), 0.5f, 0.5f);
    p.put(new TogglePort(), 0.25f, 0.25f);
    PhyWall.PhyWindow qw = p.put(new Gridding(new Label("HaiQ"), new AutoSurface<>(q), new LabeledPane("input", new Port((float[] i) -> {
        System.arraycopy(i, 0, in, 0, i.length);
    })), new Gridding(VERTICAL, new AutoUpdateMatrixView(in), new AutoUpdateMatrixView(q.ae.x), new AutoUpdateMatrixView(q.ae.W), new AutoUpdateMatrixView(q.ae.y)), new Gridding(VERTICAL, new AutoUpdateMatrixView(q.q), new AutoUpdateMatrixView(q.et))), 1, 1);
    Loop.of(() -> {
        lerpVector.update();
        q.act((((float) Math.random()) - 0.5f) * 2, in);
    }).runFPS(25);
}

Example 2 with HaiQae

use of jcog.learn.ql.HaiQae in project narchy by automenta.

the class TrackXY method main.

public static void main(String[] args) {
    boolean nars = true;
    boolean rl = false;
    int dur = 1;
    NARS nb = new NARS().exe(new UniExec(64)).time(new CycleTime().dur(dur)).index(// new HijackConceptIndex(4 * 1024, 4)
    new CaffeineIndex(32 * 1024));
    NAR n = nb.get();
    n.termVolumeMax.set(20);
    // n.priDefault(BELIEF, 0.2f);
    // n.priDefault(GOAL, 0.5f);
    n.activationRate.set(0.2f);
    // n.forgetRate.set(0.9f);
    TrackXY t = new TrackXY(4, 4);
    n.on(t);
    int experimentTime = 8048;
    n.synch();
    if (rl) {
        new RLBooster(t, // HaiQ::new,
        HaiQae::new, // RandomAgent::new,
        1);
        t.curiosity.set(0);
    }
    if (nars) {
        // Param.DEBUG = true;
        // n.log();
        // for (String action : new String[]{"up", "down", "left", "right"}) {
        // //n.goal($.the(action), Tense.Present, 0f, 0.1f);
        // n.goal($.the(action), Tense.Present, 1f, 0.1f);
        // }
        Deriver d = new Deriver(Derivers.rules(// 1,
        1, 8, n, // "list.nal",
        "motivation.nal"), n);
        d.conceptsPerIteration.set(32);
        n.timeFocus.set(2);
        ConjClustering cjB = new ConjClustering(n, BELIEF, // (tt)->true,
        (tt) -> tt.isInput(), 4, 16);
        // ConjClustering cjG = new ConjClustering(n, GOAL,
        // (tt)->true,
        // //(tt) -> tt.isInput(),
        // 5, 16);
        // Implier ii = new Implier(t , 0, 1);
        // ArithmeticIntroduction ai = new ArithmeticIntroduction(4, n);
        window(new Gridding(new AutoSurface(d), new AutoSurface(cjB)), 400, 300);
        n.onTask(tt -> {
            if (tt instanceof DerivedTask && tt.isGoal()) {
                System.out.println(tt.proof());
            }
        });
    }
    // n.log();
    // n.startFPS(fps);
    // t.runFPS(fps);
    n.onCycle(t);
    final double[] rewardSum = { 0 };
    n.onCycle(() -> {
        rewardSum[0] += t.reward;
    });
    n.runLater(() -> {
        window(Vis.top(n), 800, 250);
        NAgentX.chart(t);
        window(new CameraSensorView(t.cam, n) {

            @Override
            protected void paint(GL2 gl, int dtMS) {
                super.paint(gl, dtMS);
                RectFloat2D at = cellRect(t.sx, t.sy, 0.5f, 0.5f);
                gl.glColor4f(1, 0, 0, 0.9f);
                Draw.rect(gl, at.move(x(), y(), 0.01f));
            }
        }.withControls(), 800, 800);
    });
    n.run(experimentTime);
// n.startFPS(10f);
// t.runFPS(10f);
// System.out.println(
// 
// n4(rewardSum[0] / n.time()) + " avg reward");
// System.exit(0);
}

Example 3 with HaiQae

use of jcog.learn.ql.HaiQae in project narchy by automenta.

the class HaiQMixAgent method act.

@Override
public void act(Tensor in, float score, ArrayTensor out) {
    if (agent == null) {
        agent = new HaiQae(in.volume(), in.volume() / 2, out.volume() * 2);
    }
    int action = agent.act(score, in.get());
    if (action == -1)
        // error
        return;
    int which = action / 2;
    out.set(Util.clamp(out.get(which) + ((action % 2 == 0) ? (+1) : (-1)) * delta, -1, +1), which);
}